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Breast cancer is a heterogeneous disease. Tumor cells and associated healthy cells form ecosystems that determine disease progression and response to therapy. To characterize features of breast cancer ecosystems and their associations with clinical data, we analyzed 144 human breast tumor and 50 non-tumor tissue samples using mass cytometry. The expression of 73 proteins in 26 million cells was evaluated using tumor and immune cell-centric antibody panels. Tumors displayed individuality in tumor cell composition, including phenotypic abnormalities and phenotype dominance. Relationship analyses between tumor and immune cells revealed characteristics of ecosystems related to immunosuppression and poor prognosis. High frequencies of PD-L1+ tumor-associated macrophages and exhausted T cells were found in high-grade ER+ and ER− tumors. This large-scale, single-cell atlas deepens our understanding of breast tumor ecosystems and suggests that ecosystem-based patient classification will facilitate identification of individuals for precision medicine approaches targeting the tumor and its immunoenvironment.
ISSN:0092-8674
ISSN:1097-4172
Cell, 177 (5)
mass cytometry, breast cancer; tumor ecosystem; tumor heterogeneity; immunosuppression; T cell; macrophage; single-cell analysis; mass cytometry, cell analysis, Breast Neoplasms, macrophage, Article, B7-H1 Antigen, Disease-Free Survival, Lymphocytes, Tumor-Infiltrating, breast cancer, 1300 General Biochemistry, Genetics and Molecular Biology, Cell Line, Tumor, tumor heterogeneity, Immune Tolerance, Tumor Microenvironment, Humans, single-cell analysis, single, immunosuppression, Macrophages, T cell, 10124 Institute of Molecular Life Sciences, Neoplasm Proteins, Survival Rate, tumor ecosystem, 570 Life sciences; biology, Female, 11493 Department of Quantitative Biomedicine
mass cytometry, breast cancer; tumor ecosystem; tumor heterogeneity; immunosuppression; T cell; macrophage; single-cell analysis; mass cytometry, cell analysis, Breast Neoplasms, macrophage, Article, B7-H1 Antigen, Disease-Free Survival, Lymphocytes, Tumor-Infiltrating, breast cancer, 1300 General Biochemistry, Genetics and Molecular Biology, Cell Line, Tumor, tumor heterogeneity, Immune Tolerance, Tumor Microenvironment, Humans, single-cell analysis, single, immunosuppression, Macrophages, T cell, 10124 Institute of Molecular Life Sciences, Neoplasm Proteins, Survival Rate, tumor ecosystem, 570 Life sciences; biology, Female, 11493 Department of Quantitative Biomedicine
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 639 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 0.1% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.01% |